OpenRaiser/Intern-Atlas huggingface dataset:
Spectral Decompositions using One-Homogeneous Functionals
Venue: arXiv cs.NA 2016
Year: 2016

This paper discusses the use of absolutely one-homogeneous regularization functionals in a variational, scale space, and inverse scale space setting to define a nonlinear spectral decomposition of input data. We present several theoretical results that explain the relation between the different definitions. Additionally, results on the orthogonality of the decomposition, a Parseval-type identity and the notion of generalized (nonlinear) eigenvectors closely link our nonlinear multiscale decompositions to the well-known linear filtering theory. Numerical results are used to illustrate our findings.
Novel velocity model to improve indoor localization using inertial navigation with sensors on a smartphone
Venue: arXiv cs.OH 2016
Year: 2016

We present a generalized velocity model to improve localization when using an Inertial Navigation System (INS). This algorithm was applied to correct the velocity of a smart phone based indoor INS system to increase the accuracy by counteracting the accumulation of large drift caused by sensor reading errors. We investigated the accuracy of the algorithm with three different velocity models which were derived from the actual velocity measured at the hip of walking person. Our results show that the proposed method with Gaussian velocity model achieves competitive accuracy with a 50\% less variance over Step and Heading approach proving the accuracy and robustness of proposed method. We also investigated the frequency of applying corrections and found that a minimum of 5\% corrections per step is sufficient for improved accuracy. The proposed method is applicable in indoor localization and tracking applications based on smart phone where traditional approaches such as GNSS suffers from many issues.
A Delay Efficient Multiclass Packet Scheduler for Heterogeneous M2M Uplink
Venue: arXiv cs.NI 2016
Year: 2016

The sensory traffic in Machine-to-Machine (M2M) communications has fairly heterogeneous service delay requirements. Therefore, we study the delay-performance of a heterogeneous M2M uplink from the sensors to a M2M application server (AS) via M2M aggregators (MA). We classify the heterogeneous M2M traffic aggregated at AS into multiple Periodic Update (PU) and Event Driven (ED) classes. The PU arrivals are periodic and need to be processed by a prespecified firm service deadline whereas the ED arrivals are random with firm or soft real-time or non real-time service requirements. We use step and sigmoidal functions to represent the service utility for PU and ED packets respectively. We propose a delay efficient multiclass packet scheduling heuristic that aims to maximize a proportionally fair system utility metric. Specifically, the proposed scheduler prioritizes service to ED data while ensuring that the PU packets meet their service deadline. It also minimizes successive PU failures for critical applications by penalizing their occurrences. Furthermore, the failed PU packets are immediately cleared from the system so as to reduce network congestion. Using extensive simulations, we show that the proposed scheduler outperforms popular packet schedulers and the performance gap increases with heterogeneity in latency requirements and with greater penalty for PU failures in critical applications.
Adding Real-time Capabilities to a SML Compiler
Venue: arXiv cs.PL 2016
Year: 2016

There has been much recent interest in adopting functional and reactive programming for use in real-time system design. Moving toward a more declarative methodology for developing real-time systems purports to improve the fidelity of software. To study the benefits of functional and reactive programming for real-time systems, real-time aware functional compilers and language runtimes are required. In this paper we examine the necessary changes to a modern Standard ML compiler, MLton, to provide basic support for real-time execution. We detail our current progress in modifying MLton with a threading model that supports priorities, a chunked object model to support real-time garbage collection, and low level modification to execute on top of a real-time operating system. We present preliminary numbers and our work in progress prototype, which is able to boot ML programs compiled with MLton on x86 machines.
A Unified Inner Bound for the Two-Receiver Memoryless Broadcast Channel with Channel State and Message Side Information
Venue: arXiv cs.IT 2016
Year: 2016

We consider the two-receiver memoryless broadcast channel with states where each receiver requests both common and private messages, and may know part of the private message requested by the other receiver as receiver message side information (RMSI). We address two categories of the channel (i) channel with states known causally to the transmitter, and (ii) channel with states known non-causally to the transmitter. Starting with the channel without RMSI, we first propose a transmission scheme and derive an inner bound for the causal category. We then unify our inner bound for the causal category and the best-known inner bound for the non-causal category, although their transmission schemes are different. Moving on to the channel with RMSI, we first apply a pre-coding to the transmission schemes of the causal and non-causal categories without RMSI. We then derive a unified inner bound as a result of having a unified inner bound when there is no RMSI, and applying the same pre-coding to both categories. We show that our inner bound is tight for some new cases as well as the cases whose capacity region was known previously.
Enhancing Energy Minimization Framework for Scene Text Recognition with Top-Down Cues
Venue: arXiv cs.CV 2016
Year: 2016

Recognizing scene text is a challenging problem, even more so than the recognition of scanned documents. This problem has gained significant attention from the computer vision community in recent years, and several methods based on energy minimization frameworks and deep learning approaches have been proposed. In this work, we focus on the energy minimization framework and propose a model that exploits both bottom-up and top-down cues for recognizing cropped words extracted from street images. The bottom-up cues are derived from individual character detections from an image. We build a conditional random field model on these detections to jointly model the strength of the detections and the interactions between them. These interactions are top-down cues obtained from a lexicon-based prior, i.e., language statistics. The optimal word represented by the text image is obtained by minimizing the energy function corresponding to the random field model. We evaluate our proposed algorithm extensively on a number of cropped scene text benchmark datasets, namely Street View Text, ICDAR 2003, 2011 and 2013 datasets, and IIIT 5K-word, and show better performance than comparable methods. We perform a rigorous analysis of all the steps in our approach and analyze the results. We also show that state-of-the-art convolutional neural network features can be integrated in our framework to further improve the recognition performance.
Graph Editing to a Given Degree Sequence
Venue: arXiv cs.DS 2016
Year: 2016

We investigate the parameterized complexity of the graph editing problem called Editing to a Graph with a Given Degree Sequence, where the aim is to obtain a graph with a given degree sequence σby at most k vertex or edge deletions and edge additions. We show that the problem is W[1]-hard when parameterized by k for any combination of the allowed editing operations. From the positive side, we show that the problem can be solved in time 2^{O(k(Δ+k)^2)}n^2 log n for n-vertex graphs, where Δ=max σ, i.e., the problem is FPT when parameterized by k+Δ. We also show that Editing to a Graph with a Given Degree Sequence has a polynomial kernel when parameterized by k+Δif only edge additions are allowed, and there is no polynomial kernel unless NP\subseteq coNP/poly for all other combinations of allowed editing operations.
Blue hypertext is a perfect design decision: No perceptual disadvantage in reading and successful highlighting of relevant information
Venue: arXiv cs.HC 2016
Year: 2016

Highlighted text in the Internet (i.e. Hypertext) is predominantly blue and underlined. The percept of these hypertext characteristics were heavily questioned by applied research and empirical tests resulted in inconclusive results. The ability to identify blue text in foveal and parafoveal vision was identified as potentially constrained by the low number of foveally centered blue light sensitive retinal cells. The present study investigates if foveal and parafoveal perceptibility of hypertext is reduced during reading. A silent-sentence reading study with simultaneous eye movement recordings and the invisible boundary paradigm, which allows the investigation of foveal and parafoveal perceptibility, separately, was realized. Target words in sentences were presented in either black or blue and either underlined or normal. No effect of color and underlining, but a preview benefit could be detected for first pass reading measures (comparing fixation times after degraded vs. un- degraded parafoveal previews). Fixation time measures that included re-reading (i.e., total viewing times) showed, in addition to a preview effect, a reduced fixation time for not highlighted (black not underlined) in contrast to highlighted target words (either blue or underlined or both). Thus, the present pattern reflects no detectable perceptual disadvantage of hyperlink stimuli but increased attraction of attention resources, after first pass reading, through highlighting. Blue or underlined text allows readers to easily perceive hypertext and at the same time readers re-visited hypertext longer as a consequence of highlighting. On the basis of the present evidence blue hypertext can be safely recommended to web designers for future use.
Graph Fourier Transform based on Directed Laplacian
Venue: arXiv cs.IT 2016
Year: 2016

In this paper, we redefine the Graph Fourier Transform (GFT) under the DSP$_\mathrm{G}$ framework. We consider the Jordan eigenvectors of the directed Laplacian as graph harmonics and the corresponding eigenvalues as the graph frequencies. For this purpose, we propose a shift operator based on the directed Laplacian of a graph. Based on our shift operator, we then define total variation of graph signals, which is used in frequency ordering. We achieve natural frequency ordering and interpretation via the proposed definition of GFT. Moreover, we show that our proposed shift operator makes the LSI filters under DSP$_\mathrm{G}$ to become polynomial in the directed Laplacian.
Implicit equations of non-degenerate rational Bezier quadric triangles
Venue: arXiv cs.GR 2016
Year: 2016

In this paper we review the derivation of implicit equations for non-degenerate quadric patches in rational Bezier triangular form. These are the case of Steiner surfaces of degree two. We derive the bilinear forms for such quadrics in a coordinate-free fashion in terms of their control net and their list of weights in a suitable form. Our construction relies on projective geometry and is grounded on the pencil of quadrics circumscribed to a tetrahedron formed by vertices of the control net and an additional point which is required for the Steiner surface to be a non-degenerate quadric.
Optimal Collision/Conflict-free Distance-2 Coloring in Synchronous Broadcast/Receive Tree Networks
Venue: arXiv cs.DC 2016
Year: 2016

This article is on message-passing systems where communication is (a) synchronous and (b) based on the "broadcast/receive" pair of communication operations. "Synchronous" means that time is discrete and appears as a sequence of time slots (or rounds) such that each message is received in the very same round in which it is sent. "Broadcast/receive" means that during a round a process can either broadcast a message to its neighbors or receive a message from one of them. In such a communication model, no two neighbors of the same process, nor a process and any of its neighbors, must be allowed to broadcast during the same time slot (thereby preventing message collisions in the first case, and message conflicts in the second case). From a graph theory point of view, the allocation of slots to processes is know as the distance-2 coloring problem: a color must be associated with each process (defining the time slots in which it will be allowed to broadcast) in such a way that any two processes at distance at most 2 obtain different colors, while the total number of colors is "as small as possible". The paper presents a parallel message-passing distance-2 coloring algorithm suited to trees, whose roots are dynamically defined. This algorithm, which is itself collision-free and conflict-free, uses $Δ+ 1$ colors where $Δ$ is the maximal degree of the graph (hence the algorithm is color-optimal). It does not require all processes to have different initial identities, and its time complexity is $O(d Δ)$, where d is the depth of the tree. As far as we know, this is the first distributed distance-2 coloring algorithm designed for the broadcast/receive round-based communication model, which owns all the previous properties.
An Optimal Block Diagonal Preconditioner for Heterogeneous Saddle Point Problems in Phase Separation
Venue: arXiv cs.NA 2016
Year: 2016

The phase separation processes are typically modeled by Cahn-Hilliard equations. This equation was originally introduced to model phase separation in binary alloys, where phase stands for concentration of different components in alloy. When the binary alloy under preparation is subjected to a rapid reduction in temperature below a critical temperature, it has been experimentally observed that the concentration changes from a mixed state to a visibly distinct spatially separated two phase for binary alloy. This rapid reduction in the temperature, the so-called "deep quench limit", is modeled effectively by obstacle potential. The discretization of Cahn-Hilliard equation with obstacle potential leads to a block $2 \times 2$ {\em non-linear} system, where the $(1,1)$ block has a non-linear and non-smooth term. Recently a globally convergent Newton Schur method was proposed for the non-linear Schur complement corresponding to this non-linear system. The proposed method is similar to an inexact active set method in the sense that the active sets are first approximately identified by solving a quadratic obstacle problem corresponding to the $(1,1)$ block of the block $2 \times 2$ system, and later solving a reduced linear system by annihilating the rows and columns corresponding to identified active sets. For solving the quadratic obstacle problem, various optimal multigrid like methods have been proposed. In this paper, we study a non-standard norm that is equivalent to applying a block diagonal preconditioner to the reduced linear systems. Numerical experiments confirm the optimality of the solver and convergence independent of problem parameters on sufficiently fine mesh.
Energy-Aware Traffic Offloading for Green Heterogeneous Networks
Venue: arXiv cs.NI 2016
Year: 2016

With small cell base stations (SBSs) densely deployed in addition to conventional macro base stations (MBSs), the heterogeneous cellular network (HCN) architecture can effectively boost network capacity. To support the huge power demand of HCNs, renewable energy harvesting technologies can be leveraged. In this paper, we aim to make efficient use of the harvested energy for on-grid power saving while satisfying the quality of service (QoS) requirement. To this end, energy-aware traffic offloading schemes are proposed, whereby user associations, ON-OFF states of SBSs, and power control are jointly optimized according to the statistical information of energy arrival and traffic load. Specifically, for the single SBS case, the power saving gain achieved by activating the SBS is derived in closed form, based on which the SBS activation condition and optimal traffic offloading amount are obtained. Furthermore, a two-stage energy-aware traffic offloading (TEATO) scheme is proposed for the multiple-SBS case, considering various operating characteristics of SBSs with different power sources. Simulation results demonstrate that the proposed scheme can achieve more than 50% power saving gain for typical daily traffic and solar energy profiles, compared with the conventional traffic offloading schemes.
Geometric Integration Over Irregular Domains with topologic Guarantees
Venue: arXiv cs.NA 2016
Year: 2016

Implicitly described domains are a well established tool in the simulation of time dependent problems, e.g. using level-set methods. In order to solve partial differential equations on such domains, a range of numerical methods was developed, e.g. the Immersed Boundary method, Unfitted Finite Element or Unfitted discontinuous Galerkin methods, eXtended or Generalised Finite Element methods, just to name a few. Many of these methods involve integration over cut-cells or their boundaries, as they are described by sub-domains of the original level-set mesh. We present a new algorithm to geometrically evaluate the integrals over domains described by a first-order, conforming level-set function. The integration is based on a polyhedral reconstruction of the implicit geometry, following the concepts of the Marching Cubes algorithm. The algorithm preserves various topological properties of the implicit geometry in its polyhedral reconstruction, making it suitable for Finite Element computations. Numerical experiments show second order accuracy of the integration. An implementation of the algorithm is available as free software, which allows for an easy incorporation into other projects. The software is in productive use within the DUNE framework.
Non-orthogonal Multiple Access in Large-Scale Underlay Cognitive Radio Networks
Venue: arXiv cs.IT 2016
Year: 2016

In this paper, non-orthogonal multiple access (NOMA) is applied to large-scale underlay cognitive radio (CR) networks with randomly deployed users. In order to characterize the performance of the considered network, new closed-form expressions of the outage probability are derived using stochastic-geometry. More importantly, by carrying out the diversity analysis, new insights are obtained under the two scenarios with different power constraints: 1) fixed transmit power of the primary transmitters (PTs), and 2) transmit power of the PTs being proportional to that of the secondary base station. For the first scenario, a diversity order of $m$ is experienced at the $m$-th ordered NOMA user. For the second scenario, there is an asymptotic error floor for the outage probability. Simulation results are provided to verify the accuracy of the derived results. A pivotal conclusion is reached that by carefully designing target data rates and power allocation coefficients of users, NOMA can outperform conventional orthogonal multiple access in underlay CR networks.
Compressing combinatorial objects
Venue: arXiv cs.IT 2016
Year: 2016

Most of the world's digital data is currently encoded in a sequential form, and compression methods for sequences have been studied extensively. However, there are many types of non-sequential data for which good compression techniques are still largely unexplored. This paper contributes insights and concrete techniques for compressing various kinds of non-sequential data via arithmetic coding, and derives re-usable probabilistic data models from fairly generic structural assumptions. Near-optimal compression methods are described for certain types of permutations, combinations and multisets; and the conditions for optimality are made explicit for each method.
Compressed Sensing-based Pilot Assignment and Reuse for Mobile UEs in mmWave Cellular Systems
Venue: arXiv cs.IT 2016
Year: 2016

Technologies for mmWave communication are at the forefront of investigations in both industry and academia, as the mmWave band offers the promise of orders of magnitude additional available bandwidths to what has already been allocated to cellular networks. The much larger number of antennas that can be supported in a small footprint at mmWave bands can be leveraged to harvest massive-MIMO type beamforming and spatial multiplexing gains. Similar to LTE systems, two prerequisites for harvesting these benefits are detecting users and acquiring user channel state information (CSI) in the training phase. However, due to the fact that mmWave channels encounter much harsher propagation and decorrelate much faster, the tasks of user detection and CSI acquisition are both imperative and much more challenging than in LTE bands. In this paper, we investigate the problem of fast user detection and CSI acquisition in the downlink of small cell mmWave networks. We assume TDD operation and channel-reciprocity based CSI acquisition. To achieve densification benefits we propose pilot designs and channel estimators that leverage a combination of aggressive pilot reuse with fast user detection at the base station and compressed sensing channel estimation. As our simulations show, the number of users that can be simultaneously served by the entire mmWave-band network with the proposed schemes increases substantially with respect to traditional compressed sensing based approaches with conventional pilot reuse.
Ultra-Reliable Cloud Mobile Computing with Service Composition and Superposition Coding
Venue: arXiv cs.IT 2016
Year: 2016

An emerging requirement for 5G systems is the ability to provide wireless ultra-reliable communication (URC) services with close-to-full availability for cloud-based applications. Among such applications, a prominent role is expected to be played by mobile cloud computing (MCC), that is, by the offloading of computationally intensive tasks from mobile devices to the cloud. MCC allows battery-limited devices to run sophisticated applications, such as for gaming or for the "tactile" internet. This paper proposes to apply the framework of reliable service composition to the problem of optimal task offloading in MCC over fading channels, with the aim of providing layered, or composable, services at differentiated reliability levels. Inter-layer optimization problems, encompassing offloading decisions and communication resources, are formulated and addressed by means of successive convex approximation methods. The numerical results demonstrate the energy savings that can be obtained by a joint allocation of computing and communication resources, as well as the advantages of layered coding at the physical layer and the impact of channel conditions on the offloading decisions.